【摘要】：混合式教學(xué)模式已逐步在國內(nèi)普通高校推廣和開展,成為課程教學(xué)模式改革的主要方向。隨著信息技術(shù)的發(fā)展,大數(shù)據(jù)的概念和價(jià)值理念逐步被大眾所接受,并且,已經(jīng)滲透到醫(yī)學(xué)、建筑、金融、教育等各個(gè)領(lǐng)域。在整個(gè)教育活動過程中產(chǎn)生的,可用于發(fā)展教育、創(chuàng)新教育、優(yōu)化教育,擁有無法衡量的潛在價(jià)值的所有教育數(shù)據(jù),都是大數(shù)據(jù)的子集,都是教育大數(shù)據(jù)。教育大數(shù)據(jù)分為廣義的教育大數(shù)據(jù)和狹義的教育大數(shù)據(jù)。廣義的教育大數(shù)據(jù)是指一切與教育相關(guān)的或教育過程中產(chǎn)生的所有數(shù)據(jù):主要包括教育活動過程中的數(shù)據(jù)、在教育管理活動中采集到的數(shù)據(jù)、在科學(xué)研究活動中采集到的數(shù)據(jù)、在校園生活中產(chǎn)生的數(shù)據(jù)等所有來源于教育活動中學(xué)生的行為數(shù)據(jù);狹義的教育大數(shù)據(jù)則可以是與學(xué)生學(xué)習(xí)相關(guān)的一切數(shù)據(jù),即學(xué)生個(gè)人大數(shù)據(jù):主要包括線上操作日志,線上業(yè)務(wù)數(shù)據(jù);線下的課堂實(shí)錄、紙質(zhì)資料(獲獎證書、請假條、小紙條)等。本文的研究數(shù)據(jù)就是狹義的教育大數(shù)據(jù)。目前,教育領(lǐng)域大數(shù)據(jù)應(yīng)用的大體狀況為:教師教學(xué)評價(jià)、決策絕大多數(shù)都是以教學(xué)者單方面的主觀判斷作為依據(jù),學(xué)生反思的依據(jù)也僅僅只有成績。針對上述狀況,本文嘗試探索混合式教學(xué)模式下學(xué)生個(gè)人大數(shù)據(jù)的應(yīng)用。本文主要在混合式教學(xué)模式下,從教師學(xué)生評價(jià)、教學(xué)反饋、學(xué)生反思三個(gè)方面對學(xué)生個(gè)人大數(shù)據(jù)在教和學(xué)的應(yīng)用展開研究。本文第一部分提出了在混合式教學(xué)模式研究學(xué)生個(gè)人大數(shù)據(jù)的意義;第二部分闡述了混合式教學(xué)模式的特征,并對混合式教學(xué)支撐平臺——云課堂的功能進(jìn)行了介紹;第三部分主要介紹學(xué)生個(gè)人大數(shù)據(jù)的應(yīng)用模型,重點(diǎn)說明了存儲模型和分析模型;第四部分詳細(xì)討論了學(xué)生個(gè)人大數(shù)據(jù)在教師對學(xué)生的評價(jià)、教師利用數(shù)據(jù)進(jìn)行教學(xué)反思,調(diào)整教學(xué)策略及學(xué)生利用綜合性數(shù)據(jù)以及過程性數(shù)據(jù)進(jìn)行學(xué)習(xí)反思、學(xué)習(xí)計(jì)劃調(diào)整三個(gè)方面的具體的應(yīng)用。
[Abstract]:The mixed teaching mode has been popularized and carried out gradually in the domestic universities and colleges, and has become the main direction of the reform of the curriculum teaching mode. With the development of information technology, big data's concept and value concept are gradually accepted by the public, and have penetrated into the fields of medicine, architecture, finance, education and so on. All the educational data, which can be used to develop education, innovate education, optimize education and have unmeasurable potential value, are a subset of big data and all of them are educational big data. Educational big data is divided into the broad sense of educational big data and the narrow sense of educational big data. In a broad sense, educational big data refers to all the data related to education or produced in the process of education: mainly including the data in the course of educational activities, the data collected in educational management activities, and the data collected in scientific research activities. The data generated in the campus life are all derived from the behavior data of the middle school students in the educational activities; In a narrow sense, big data can be all the data related to the students' study, that is, the student individual big data: mainly includes the online operation log, the on-line business data; Below-line classroom record, paper materials (award-winning certificate, note, note) and so on. The research data of this paper is educational big data in narrow sense. At present, the general situation of big data's application in the field of education is as follows: teachers' teaching evaluation and decision-making are mostly based on the unilateral subjective judgment of the teacher, and the students' reflection is based on only achievements. In view of the above situation, this paper tries to explore the application of individual big data in the mixed teaching mode. In this paper, the application of individual big data in teaching and learning is studied from three aspects: teacher and student evaluation, teaching feedback and student reflection under the mixed teaching mode. The first part of this paper puts forward the significance of studying individual big data in the mixed teaching mode, the second part expounds the characteristics of the mixed teaching model, and introduces the function of cloud classroom, which is the supporting platform of hybrid teaching. The third part mainly introduces the application model of student individual big data, focusing on the storage model and analysis model; The fourth part discusses the students' individual big data's evaluation of students in detail, teachers use data to reflect on teaching, adjust teaching strategies, and students use comprehensive data and process data to reflect on learning. The specific application of learning plan adjustment in three aspects.
【學(xué)位授予單位】：華中師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：G434

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 鐘婉娟;侯浩翔;;大數(shù)據(jù)視角下教育決策機(jī)制優(yōu)化及實(shí)現(xiàn)路徑[J];教育發(fā)展研究;2016年03期

2 楊現(xiàn)民;唐斯斯;李冀紅;;發(fā)展教育大數(shù)據(jù):內(nèi)涵、價(jià)值和挑戰(zhàn)[J];現(xiàn)代遠(yuǎn)程教育研究;2016年01期

3 胥文勛;;大數(shù)據(jù)時(shí)代高校學(xué)生管理工作信息化建設(shè)現(xiàn)狀與對策[J];綿陽師范學(xué)院學(xué)報(bào);2016年01期

4 顧小清;薛耀鋒;孫妍妍;;大數(shù)據(jù)時(shí)代的教育決策研究:數(shù)據(jù)的力量與模擬的優(yōu)勢[J];中國電化教育;2016年01期

5 趙興龍;;創(chuàng)新評價(jià)體系 加速教育變革 中央電化教育館和英特爾公司共同啟動“教育大數(shù)據(jù)分析研究”項(xiàng)目[J];中國電化教育;2015年12期

6 唐雪;;“學(xué)生畫像”發(fā)掛科預(yù)警[J];大學(xué)生;2015年22期

7 穆肅;左萍萍;;信息化教學(xué)環(huán)境下課堂教學(xué)行為分析方法的研究[J];電化教育研究;2015年09期

8 唐輝軍;宋揚(yáng);熊松泉;;高校學(xué)生微博使用行為大數(shù)據(jù)分析和管理研究[J];科教文匯(上旬刊);2015年08期

9 姜強(qiáng);趙蔚;王朋嬌;王麗萍;;基于大數(shù)據(jù)的個(gè)性化自適應(yīng)在線學(xué)習(xí)分析模型及實(shí)現(xiàn)[J];中國電化教育;2015年01期

10 趙中建;張燕南;;與大數(shù)據(jù)同行的學(xué)習(xí)與教育——《大數(shù)據(jù)時(shí)代》作者舍恩伯格教授和庫克耶先生訪談[J];全球教育展望;2014年12期

相關(guān)碩士學(xué)位論文 前1條

1 黃亞紅;初中課堂學(xué)生行為觀察分析與實(shí)證研究[D];華中師范大學(xué);2016年

，

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